Labor work studies & standard determination methodology applications for effective labor resource management

Industrial Engineering (IE) has developed into a branch of knowledge that optimizes the use of the organization’s resources. Labor resource as a cost factor is included too. Today, productivity and efficiency improvement through IE techniques and tools are proven to be effective. The leveraging of critical success elements in IE programs impacts the effectiveness of resource management, especially labor resource. In formulating the best IE practices, the maturity of an organization’s IE programs, which depends on many factors including management policy, the industrial engineers’ technical skills, the manufacturing operations environment, the business climate, etc, must be considered. Yet, the overall impact is unknown. To save on labor, work must be measured and controlled. Work measurement should be used to set standards for labor productivity and resource hiring. Nowadays, direct labor workforce no longer does manual assembly work alone. Rather, they also perform non ordinary types of production work, which in the past was handled by indirect labor workforce. Smart automation has changed the labor-intensive work and non-labor-intensive work ratio in favor of the latter. Hence, setting the work standard for this emerging workforce group (non-production-direct-labor, NPDL as termed in this thesis) is needed. At present, work standard for NPDL is largely neglected due to the fact that the occurrence frequency is not consistent, hence causing the cycle time of each occurrence to vary. To add, the work scope and work expectations are vague, and the time elements of the tasks are not discrete because the work is usually carried out in groups rather than individually. This research analyzes the critical success elements in IE programs that impact the effectiveness of the use of resources as well as factory productivity, based on data accrued from Electronic Manufacturing Service (EMS) organizations. An Industrial Engineering Maturity Matrix (IEMM) is created, which enables organizations to gauge their IE maturity level. The IEMM comprises a rating system that enables the representation of the quality and condition of IE programs in four blocks, namely KPI performance management, IE tasks, IE tools and IE people-related factors. The rating uses a scale of zero to five. To address the difficulties in determining the standard time for NPDL works, a work study quadrant called ‘Data Capture-ability & Data Analyzability Quadrant’ is created. The quadrant gives the appropriate steps to comprehend the NPDL work content, characteristics, and attributes. Hence, despite the difficulty in defining the NPDL work nature, the quadrant enables the execution of work measuring steps, therefore increasing the chances of setting the suitable standard time accordingly. Both IEMM and the quadrant will contribute to the setting up of an effective IE program and the management of NPDL workforce through a proper task quantification process.